class_docstr: Dummy NMTModel wrapping individual real NMTModels.
code: def __init__(self, models, raw_probs=False):
      encoder = EnsembleEncoder(model.encoder for model in models)
      decoder = EnsembleDecoder(model.decoder for model in models)
      super(EnsembleModel, self).__init__(encoder, decoder)
      self.generator = EnsembleGenerator(
          [model.generator for model in models], raw_probs
      )
      self.models = nn.ModuleList(models)
  
imports: import torch
  import torch.nn
  from onmt.encoders.encoder import EncoderBase
  from onmt.decoders.decoder import DecoderBase
  from onmt.models import NMTModel
  import onmt.model_builder
label_desc: Use image node_id 1 to create a new EnsembleModel object from inherited base classes: NMTModel with example: obj = EnsembleModel(models, raw_probs)